Hasil untuk "Geology"

J. Field

K. Hsü, L. Montadert, D. Bernoulli et al.

C. Marshall, A. Hallam, P. Wignall

G. Keller

D. Gautier, K. Bird, R. Charpentier et al.

L. Cahen, N. Snelling

L. Johnson, C. Richards, G. Host et al.

P. Kayastha, M. Dhital, F. Smedt

J. Schopf, C. Klein

A. Keneti, B. Sainsbury

Abstract Through a review of selected published case study data from around the world, in situ conditions that contribute to rockburst events have been identified. This review was carried out to assist research associated with developing numerical modelling techniques to reproduce rockbursting within a large-scale (mine models) for predictive purposes. Contributing factors identified through the case study review include unfavourable stress states, excavation geometry (size and orientation in relation to the principal stresses) and rate and direction of advance. Factors also incorporated unfavourable rock mass characteristics that included mineralogy, contrasts in geomechanical properties, and geological intensifiers (dykes, faults, etc.).

S. Tao, Z. Pan, Shuling Tang et al.

Abstract Coalbed methane (CBM) drilling technology is critical in achieving efficient CBM development. The geological conditions for CBM development in China are complex, including special terrain, high-rank coal areas, deep coal seams, multiple superposed coal seams and coal measure gas symbiosis areas, steeply inclined coal seam areas, and tectonic coal seam areas. Therefore, it is critical to apply the optimum drilling technology in each different area. This paper first reviews the current CBM drilling technologies and gas production behaviors in China. It is found that although vertical wells and cluster well groups are common well types for CBM development in China, U-, V- and L- shaped horizontal wells and multilateral horizontal wells have been favored for CBM development in recent years. The paper then discusses the applicability of different well types to geological conditions and proposes a modification method for well design in various geologic conditions. This method uses the coal structure, Ro, in situ stress, and ratio of critical desorption pressure to the reservoir pressure as the main inputs.

G. Ohlmacher, John C. Davis

C. Richards, L. Johnson, G. Host

Youssef Gharnit, Aboubakre Outourakhte, Abdelaziz Moujane et al.

The Moroccan High Atlas ecosystems, particularly the Geopark M’goun, face increasing threats from demographic and environmental pressures, necessitating urgent assessment. The habitat mapping is carried out using remote sensing and GIS techniques, along with fieldwork and Google Earth records. Habitat ecology is established using climate data, bioclimatic levels, vegetation levels, substrate types, and elevation data. Additionally, NDVI, change detection, and supervised classification are combined to assess habitat change. As a result, the M’goun Geopark exhibits an outstinding habitat diversity; Quercus ilex (27.53%) dominates up to 3000 m, favoring limestone and dolomites in subhumid zones, while Juniperus phoenicea (14.78%) occupies lower altitudes (up to 2000 m) and semi-arid regions. Pinus halepensis (1.38%) flourishes between 1100 and 2000 m, mainly in detrital formations and limestone, adaptable to semi-arid and subhumid bioclimates. Juniperus thurifera (1.33%) and xerophyte cushions (6.84%) thrive at high elevations in limestone terrains within subhumid cold bioclimate variants. Secondary habitats, including Chamaerops humilis, Buxus, and Euphorbia resinifera, thrive within the primary habitats. Furthermore, Juniperus thurifera and Pinus halepensis forests are severely degraded, while Quercus ilex and Juniperus phoenicea forests, though degraded, are more resilient. This funding supports conservation initiatives in Mediterranean ecosystems, addressing the urgent preservation and restoration policies.

R. Dowling

Junchen Ye, Yuhao Mao, Ke Cheng et al.

Given the swift proliferation of structural health monitoring (SHM) technology within tunnel engineering, there is a demand on proficiently and precisely imputing the missing monitoring data to uphold the precision of disaster prediction. In contrast to other SHM datasets, the monitoring data specific to tunnel engineering exhibits pronounced spatiotemporal correlations. Nevertheless, most methodologies fail to adequately combine these types of correlations. Hence, the objective of this study is to develop spatiotemporal recurrent neural network (ST-RNN) model, which exploits spatiotemporal information to effectively impute missing data within tunnel monitoring systems. ST-RNN consists of two moduli: a temporal module employing recurrent neural network (RNN) to capture temporal dependencies, and a spatial module employing multilayer perceptron (MLP) to capture spatial correlations. To confirm the efficacy of the model, several commonly utilized methods are chosen as baselines for conducting comparative analyses. Furthermore, parametric validity experiments are conducted to illustrate the efficacy of the parameter selection process. The experimentation is conducted using original raw datasets wherein various degrees of continuous missing data are deliberately introduced. The experimental findings indicate that the ST-RNN model, incorporating both spatiotemporal modules, exhibits superior interpolation performance compared to other baseline methods across varying degrees of missing data. This affirms the reliability of the proposed model.

Yuandong Li, Zhijie Han, Rui Yang et al.

Study region: The Dajing and Xiaojing karst underground river system is the longest underground river in Guizhou Province, Southwest of China，located around the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Study focus: The water quality of underground rivers around the FAST being affected by multiple anthropogenic activities. The underground river system is an extremely non-homogeneous and anisotropic media with complex hydrodynamic and hydrochemical responses. Multi-tools (hydrochemistry, water isotope, sulfur isotope and statistical methods) were applied to accurate identification and quantification of the proportions, spatiotemporal evolution and mechanisms of karst aquifer impacted by different anthropogenic activities. New hydrological insights for the region: The synchronous variations of δ18O, δD, d-excess and δ34SO42- in the effluent and the underground rivers suggested that the underground rivers are influenced by anthropogenic activities. The relationships of ionic ratios revealed that agricultural activities, effluent from the sewage treatment plant, and water-rock interactions control the hydro-chemical characteristics of the underground river system with a distinct spatiotemporal differentiation. The response time for the water quality of Dajing and Xiaojing underground river to anthropogenic impacts were 24 and 27 days, respectively. Spatially, the PCA-ACPS-MLR and MixSIAR indicated that more impacts of anthropogenic activities on Xiaojing underground river than Dajing underground river system. A quantification of spatiotemporal response differentiation provides new insights into the precise identification and prevention of pollution in karst underground rivers.

K. Bjørlykke

D. Galloway, David R. Jones, S. Ingebritsen

P. Calcagno, J. Chilès, G. Courrioux et al.